Sleep hygiene Post-Survey 5/3/2021

library(ggplot2)
library(dplyr)

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library(tidyverse)

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library(arsenal)
library(data.table)

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library(expss)

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sleephygiene <- read_csv("/Users/Ivanics/Desktop/SPH/4th term/HealthComm/Qualtrics post/Sleep Hygiene Post-Survey_May 4, 2021_09.05.csv")

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sleephygiene$StartDate <- lubridate::ymd_hms(sleephygiene$StartDate)

## Warning: 2 failed to parse.

#Filter to include only responses beyond this time
sleephygiene <- sleephygiene %>% filter(StartDate >= "2021-04-29 00:00:00")

#Select out the variables we need
sleephygiene <- sleephygiene %>% select(Progress, `Duration (in seconds)`, Finished, LocationLatitude, LocationLongitude, DistributionChannel, UserLanguage, Q1, Q2, Q3, Q2_5_TEXT, Q4, Q5, Q6, Q37, Q92, Q93, Q94,  Q38, Q39, Q10_2, Q10_3, Q9, Q61, Q84, Q85, Q81, Q63, Q96_1, Q96_2, Q96_3, Q96_4, Q96_5, Q96_6, Q96_7, Q96_8, Q95, Q83, Q82, Q69, Q62, Q64, Q90, Q91, Q89_1, Q67_1, Q67_2, Q67_3, Q75_1, Q75_2, Q75_3, Q68, Q70, Q70_18_TEXT, Q87, Q71, Q72, Q79, Q79_5_TEXT, Q74, Q73, Q73_5_TEXT, Q59_1, Q59_2, Q59_3, Q59_4, Q44_1, Q44_2, Q44_3, Q44_4, Q44_5, Q44_6, Q44_7, Q44_8, Q44_9, Q52)

sleephygiene <- rowid_to_column(sleephygiene, "ID")

#General factor recoding
sleephygiene <- sleephygiene %>% mutate(
  Q1_consent = factor(Q1)) %>%
  mutate(Q2_program = factor(Q2)) %>%
  mutate(Q3_role = factor(Q3)) %>%
  mutate(Q4_gender = factor(Q4)) %>%
  mutate(Q5_age = factor(Q5)) %>%
  mutate(Q6_numberinhousehold = as.numeric(Q6)) %>%
  mutate(Q37_employed = factor(Q37)) %>%
  mutate(Q92_notSPHemployed = factor(Q92)) %>%
  mutate(Q93_worksetting = factor(Q93)) %>%
  mutate(Q94_dayornight = factor(Q94)) %>%
  mutate(Q38_worksetting = factor(Q38)) %>%
  mutate(Q39_dayornight = factor(Q39)) %>%
  mutate(Q10_hoursofsleeplast5workdays = as.numeric(Q10_2)) %>%
  mutate(Q10_hoursofsleeppastweekend = as.numeric(Q10_3)) %>%
  mutate(Q9_howoftensleepypastmonth = factor(Q9)) %>%
  mutate(Q61_howoftensleepypasttwoweeks = factor(Q61)) %>%
  mutate(Q84_awareofhowtoimprovesleepquality = factor(Q84)) %>%
  mutate(Q81_seenorheardfromGNbloombergcampaign = factor(Q81)) %>%
  mutate(Q63_recalltoolsfreetect = factor(Q63)) %>%
  mutate(Q96_picture1 = factor(Q96_1)) %>%
  mutate(Q96_picture2 = factor(Q96_2)) %>%
  mutate(Q96_picture3 = factor(Q96_3)) %>%
  mutate(Q96_picture4 = factor(Q96_4)) %>%
  mutate(Q96_picture5 = factor(Q96_5)) %>%
  mutate(Q96_picture6 = factor(Q96_6)) %>%
  mutate(Q96_picture7 = factor(Q96_7)) %>%
  mutate(Q96_picture8 = factor(Q96_8)) %>%
  mutate(Q95_talkedtoanyone = factor(Q95)) %>%
  mutate(Q82_knowanyonewhoengaged = factor(Q82)) %>%
  mutate(Q69_didyouengagewiththecampaign = factor(Q69)) %>%
  mutate(Q90_areyouhappywithyoursleepquality_awareofcampaign = factor(Q90)) %>%
  mutate(Q91_areyouhappywithyoursleepquality_notawareofcampaign = factor(Q91)) %>%
  mutate(Q89_ratesleepquality_notawareofcampaign = factor(Q89_1)) %>%
  mutate(Q67_move30minutes = as.numeric(Q67_1)) %>%
  mutate(Q67_breathing = as.numeric(Q67_2)) %>%
  mutate(Q67_powerdown = as.numeric(Q67_2)) %>%
  mutate(Q75_moving = factor(Q75_1)) %>%
  mutate(Q75_breathing = factor(Q75_2)) %>%
  mutate(Q75_powerdown = factor(Q75_3)) %>%
  mutate(Q68_timing = factor(Q68)) %>%
  mutate(Q87_idealtime = factor(Q87)) %>%
  mutate(Q74_rafflemotivating = factor(Q74)) %>%
  mutate(Q75_moving = factor(Q75_1)) %>%
  mutate(Q59_canmaintainhealthysleephabits = factor(Q59_1)) %>%
  mutate(Q59_cancutoutscreen = factor(Q59_2)) %>%
  mutate(Q59_canexercise = factor(Q59_3)) %>%
  mutate(Q59_canparticipateinbreathing = factor(Q59_4)) %>%
  mutate(Q44_goodnightsleepisimportant = factor(Q44_1)) %>%
  mutate(Q44_mentalclarity = factor(Q44_2)) %>%
  mutate(Q44_feelpositive = factor(Q44_3)) %>%
  mutate(Q44_cuttingoutscreenleadstobettersleep = factor(Q44_4)) %>%
  mutate(Q44_exercisingleadstobettersleep = factor(Q44_5)) %>%
  mutate(Q44_breathingexercisesleadstobettersleep = factor(Q44_6)) %>%
  mutate(Q44_iwillstopscreens = factor(Q44_7)) %>%
  mutate(Q44_iwillexercise = factor(Q44_8)) %>%
  mutate(Q44_iwillbreathe = factor(Q44_9)) %>%
  mutate(Q52_additionalcomments = factor(Q52))

#Q85
resp.split_85 <- strsplit(sleephygiene$Q85, ",")
lev <- unique(unlist(resp.split_85))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_85, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q85_waystoimprovesleepquality = case_when(
    Not.drinking.caffeinated.beverages.late.in.the.day == 1 ~ "Not drinking caffeinated beverages late in the day",
    Switching.off.electronics.one.hour.before.sleep == 1 ~ "Switching off electronics one hour before sleep",
    Incorporating.moderate.exercise.as.part.of.your.day == 1 ~ "Incorporating moderate exercise as part of your day",
    Increase.natural.bright.light.exposure.in.the.day == 1 ~ "Increase natural bright light exposure in the day",
    Reduce.irregular.or.long.daytime.naps == 1 ~ "Reduce irregular or long daytime naps",
    Try.to.sleep.and.wake.at.consistent.times == 1 ~ "Try to sleep and wake at consistent times",
    Take.a.melatonin.supplement == 1 ~ "Take a melatonin supplement",
    Decrease.alcohol.consumption == 1 ~ "Decrease alcohol consumption",
    Deep.breathing.exercises == 1 ~ "Deep breathing exercises"))

#Q83
resp.split_83 <- strsplit(sleephygiene$Q83, ",")
lev <- unique(unlist(resp.split_83))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_83, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q83_talkedtowho = case_when(
    Friends == 1 ~ "Friends",
    Spouse == 1 ~ "Spouse",
    Relatives == 1 ~ "Relatives",
    Colleague == 1 ~ "Colleague"))

#Q62
resp.split_62 <- strsplit(sleephygiene$Q62, ",")
lev <- unique(unlist(resp.split_62))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_62, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q62_howdidyouengage = case_when(
    Instagram.campaign == 1 ~ "Instagram campaign",
    Text.message.campaign == 1 ~ "Text message campaign",
    Word.of.mouth.discussion.with.others == 1 ~ "Word of mouth/discussion with others"))

#64
resp.split_64 <- strsplit(sleephygiene$Q64, ",")
lev <- unique(unlist(resp.split_64))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_64, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q64_whichtechniquedidyoutry = case_when(
    X.MoveMore == 1 ~ "Movemore",
    X.Breathe== 1 ~ "Breathe",
    X.PowerDown == 1 ~ "Powerdown",
    None.of.the.above == 1 ~ "None of the above"))

#70
resp.split_70 <- strsplit(sleephygiene$Q70, ",")
lev <- unique(unlist(resp.split_70))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_70, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q70_timingoftextsinconvenient = case_when(
    #Messages.were.too.frequent == 1 ~ "Messages were too frequent",
    Messages.were.too.infrequent== 1 ~ "Messages were too infrequent",
    Received.message.too.early.in.the.day == 1 ~ "Received message too early in the day",
    #Received.message.too.late.in.the.day == 1 ~ "Received message too late in the day",
    Other..please.explain.below. == 1 ~ "Other (please explain below)"))

#71
resp.split_71 <- strsplit(sleephygiene$Q71, ",")
lev <- unique(unlist(resp.split_71))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_71, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q71_whichchannelmosteducational = case_when(
    Text == 1 ~ "Text",
    Instagram == 1 ~ "Instagram"))
    #Discussion.with.others.about.the.campaign == 1 ~ "Discussion with others about the campaign",
    #None.of.the.above.1 == 1 ~ "None of the above"))

#72 - look into


#Q79
resp.split_79 <- strsplit(sleephygiene$Q79, ",")
lev <- unique(unlist(resp.split_79))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_79, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q79_moresuccessfuloutcomsuggestions = case_when(
    There.was.an.in.person.on.campus.component.to.the.campaign == 1 ~ "There was an in-person/on-campus component to the campaign",
    The.campaign.was.longer == 1 ~ "The campaign was longer",
    I.had.more.flexibility.in.my.day == 1 ~ "I had more flexibility in my day",
    There.were.subject.matter.experts.checking.in.with.me.one.on.one == 1 ~ "There were subject matter experts checking in with me one-on-one"))
    #Other == 1 ~ "Reduce irregular or long daytime naps",

#Q73
resp.split_73 <- strsplit(sleephygiene$Q73, ",")
lev <- unique(unlist(resp.split_73))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_73, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q73_hearabouthow = case_when(
    Instagram.1 == 1 ~ "Instagram",
    JHSPH.Activities.email == 1 ~ "JHSPH Activities email",
    #Class.announcement == 1 ~ "Class announcement",
    Word.of.mouth.discussion.with.others.1 == 1 ~ "Word of mouth/discussion with others"))
    #Other == 1 ~ "Reduce irregular or long daytime naps",

Plots for wakeup and sleep times

library(plotly)

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workdayssleep <- sleephygiene %>% ggplot( aes(x=Q10_hoursofsleeplast5workdays)) +
    geom_histogram( binwidth=1, fill="#69b3a2", color="#e9ecef", alpha=0.9) +
    ggtitle("Hours of sleep last five workdays") +
    theme(
      plot.title = element_text(size=32)
    ) +
  labs(x="Number of hours of sleep in the past five workdays", y="Number of participants")
ggplotly(workdayssleep)

## Warning: Removed 3 rows containing non-finite values (stat_bin).

#Plot for weekend
weekend <- sleephygiene %>% ggplot( aes(x=Q10_hoursofsleeppastweekend)) +
    geom_histogram( binwidth=1, fill="#69b3a2", color="#e9ecef", alpha=0.9) +
    ggtitle("Hours of sleep last weekend") +
    theme(
      plot.title = element_text(size=32)
    ) +
  labs(x="Number of hours of sleep in the past weekend", y="Number of participants")
ggplotly(weekend)

## Warning: Removed 3 rows containing non-finite values (stat_bin).

#Tab 1
sleephygiene$Q9_howoftensleepypastmonth <- factor(sleephygiene$Q9_howoftensleepypastmonth, levels = c("Never", "Rarely", "Sometimes", "Very often", "Always"))
sleephygiene$Q61_howoftensleepypasttwoweeks <- factor(sleephygiene$Q61_howoftensleepypasttwoweeks, levels = c("Never", "Rarely", "Sometimes", "Very often", "Always"))
sleephygiene$Q89_ratesleepquality_notawareofcampaign <- factor(sleephygiene$Q89_ratesleepquality_notawareofcampaign, levels = c("Poor", "Fair", "Good", "Excellent"))
sleephygiene$Q75_moving <- factor(sleephygiene$Q75_moving, levels = c("Extremely unhelpful", "Somewhat unhelpful", "Neither helpful nor unhelpful", "Somewhat helpful", "Extremely helpful"))
sleephygiene$Q75_breathing <- factor(sleephygiene$Q75_breathing, levels = c("Extremely unhelpful", "Somewhat unhelpful", "Neither helpful nor unhelpful", "Somewhat helpful", "Extremely helpful"))
sleephygiene$Q75_powerdown <- factor(sleephygiene$Q75_powerdown, levels = c("Extremely unhelpful", "Somewhat unhelpful", "Neither helpful nor unhelpful", "Somewhat helpful", "Extremely helpful"))
sleephygiene$Q87_idealtime <- factor(sleephygiene$Q87_idealtime, levels = c("Early morning (6:00 am - 9:00 am)", "Late morning (9:01 am - 12:00 pm)", "Early afternoon (12:01 pm - 3:00 pm)", "Late afternoon (3:01 pm - 6:00 pm)", "Early evening (6:01 pm - 9:00 pm)", "Late evening (9:01 pm - 12:00 am)", "Other (please specify)"))
sleephygiene$Q59_canmaintainhealthysleephabits <- factor(sleephygiene$Q59_canmaintainhealthysleephabits, levels = c("Not at all confident", "Somewhat confident", "Extremely confident"))
sleephygiene$Q59_cancutoutscreen <- factor(sleephygiene$Q59_cancutoutscreen, levels = c("Not at all confident", "Somewhat confident", "Extremely confident"))
sleephygiene$Q59_canexercise <- factor(sleephygiene$Q59_canexercise, levels = c("Not at all confident", "Somewhat confident", "Extremely confident"))
sleephygiene$Q59_canparticipateinbreathing <- factor(sleephygiene$Q59_canparticipateinbreathing, levels = c("Not at all confident", "Somewhat confident", "Extremely confident"))
sleephygiene$Q44_goodnightsleepisimportant <- factor(sleephygiene$Q44_goodnightsleepisimportant, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_mentalclarity <- factor(sleephygiene$Q44_mentalclarity, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_feelpositive <- factor(sleephygiene$Q44_feelpositive, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_cuttingoutscreenleadstobettersleep <- factor(sleephygiene$Q44_cuttingoutscreenleadstobettersleep, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_exercisingleadstobettersleep <- factor(sleephygiene$Q44_exercisingleadstobettersleep, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_breathingexercisesleadstobettersleep <- factor(sleephygiene$Q44_breathingexercisesleadstobettersleep, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_iwillstopscreens <- factor(sleephygiene$Q44_iwillstopscreens, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_iwillexercise <- factor(sleephygiene$Q44_iwillexercise, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_iwillbreathe <- factor(sleephygiene$Q44_iwillbreathe, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))

library(expss)
sleephygiene = apply_labels(sleephygiene,
                      Q3_role = "What is your role at Bloomberg",
                      Q4_gender = "Which best describes your gender identity?",
                      Q2_program = "What is your current program at Bloomberg?",
                      Q5_age = "How old are you?",
                      Q6_numberinhousehold = "How many people live in your household, including yourself?",
                      Q37_employed = "If you are a student at Bloomberg, are you currently employed outside of your education program?",
                      Q92_notSPHemployed = "Are you currently employed?",
                      Q93_worksetting = "Which of the following best describes your current work setting?",
                      Q94_dayornight = "Do you work day or night shifts?",
                      Q38_worksetting = "Which of the following best describes your current work setting?",
                      Q39_dayornight = "Do you work day or night shifts?",
                      Q10_hoursofsleeplast5workdays = "On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?",
                      Q10_hoursofsleeppastweekend = "On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?",
                      Q9_howoftensleepypastmonth = "How often did you feel sleepy during the day in the past month?",
                      Q61_howoftensleepypasttwoweeks = "How often did you feel sleepy during the day during the past 2 weeks?",
                      Q84_awareofhowtoimprovesleepquality = "Do you know any ways a person can improve their sleep quality?",
                      Q85_waystoimprovesleepquality = "What are some of the ways to improve sleep quality that you know?",
                      Q81_seenorheardfromGNbloombergcampaign = "In the last two-three weeks have you heard, seen, or received any information from the #GoodnightBloomberg campaign led by JHSPH students promoting better sleep?",
                      Q63_recalltoolsfreetect = "Can you recall any specific tools, techniques, or resources from the campaign? Please describe below.",
                      Q96_picture1 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 1",
                      Q96_picture2 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 2",
                      Q96_picture3 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 3",
                      Q96_picture4 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 4",
                      Q96_picture5 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 5",
                      Q96_picture6 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 6",
                      Q96_picture7 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 7",
                      Q96_picture8 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 8",
                      Q95_talkedtoanyone = "Have you talked to anyone about the #GoodnightBloomberg campaign?",
                      Q83_talkedtowho = "Please indicate with whom you talked about #GoodnightBloomberg (check all that apply).",
                      Q82_knowanyonewhoengaged = "Do you know anyone who engaged in any way with the #GoodnightBloomberg campaign about promoting better sleep?",
                      Q69_didyouengagewiththecampaign = "Did you engage in any way with the #GoodnightBloomberg campaign led by JHSPH students during the past 2 weeks?",
                      Q62_howdidyouengage = "Please select which of the following parts of the #GoodnightBloomberg campaign you engaged in:",
                      Q64_whichtechniquedidyoutry = "Which of the following techniques did you try at least once in the last 2 weeks (choose all that apply)?", 
                      Q90_areyouhappywithyoursleepquality_awareofcampaign = "Are you happy with your sleep quality overall currently?", 
                      Q91_areyouhappywithyoursleepquality_notawareofcampaign = "Are you happy with your sleep quality overall currently?", 
                      Q89_ratesleepquality_notawareofcampaign = "Please rate your sleep quality from the following options: In the last two weeks? (on average)",
                      Q67_move30minutes =  "In the last two weeks, how many days did you participate in the following techniques? Move 30 minutes total per day",
                      Q67_breathing = "In the last two weeks, how many days did you participate in the following techniques? Use a breathing exercise",
                      Q67_powerdown = "In the last two weeks, how many days did you participate in the following techniques? Power down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed",
                      Q75_moving = "How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Moving 30 minutes total per day",
                      Q75_breathing = "How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Using a breathing exercise",
                      Q75_powerdown = "How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Powering down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed",
                      Q68_timing = "Was the timing of the texts/posts convenient for you to adopt the recommended activity? ",
                      Q70_timingoftextsinconvenient = "Please provide information below about why the timing of the texts/posts was inconvenient?", 
                      Q87_idealtime = "What would have been the ideal time to receive the message (EST/EDT)?",
                      Q71_whichchannelmosteducational = "Which channel did you find the most educational?",
                      Q79_moresuccessfuloutcomsuggestions = "I think I would have had a more successful outcome (e.g. better sleep quality) if (choose all that may apply):",
                      Q74_rafflemotivating = "Did you find the raffles motivating for participation in the #GoodnightBloomberg campaign?",
                      Q73_hearabouthow = "How did you hear about the #GoodnightBloomberg campaign?",
                      Q59_canmaintainhealthysleephabits = "Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can maintain healthy sleep habits.",
                      Q59_cancutoutscreen = "Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can cut out screen use 1 hour before bed.",
                      Q59_canexercise = "Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can exercise for 30 minutes total each day.", 
                      Q59_canparticipateinbreathing = "Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can participate in a breathing exercise during the day or before bed.", 
                      Q44_goodnightsleepisimportant = "Please rate your agreement with the following statements: Getting a good night's sleep is important to me.",
                      Q44_mentalclarity = "Please rate your agreement with the following statements: Having a regular sleep routine improves mental clarity/sharpness.",
                      Q44_feelpositive = "Please rate your agreement with the following statements: I feel positive about the quality of my sleep.",
                      Q44_cuttingoutscreenleadstobettersleep = "Please rate your agreement with the following statements: I think cutting out screen use 1 hour before bed leads to better sleep.",
                      Q44_exercisingleadstobettersleep = "Please rate your agreement with the following statements: I think exercising regularly leads to better sleep.",
                      Q44_breathingexercisesleadstobettersleep = "Please rate your agreement with the following statements: I think participating in breathing exercises during the day or before bed leads to better sleep.",
                      Q44_iwillstopscreens = "Please rate your agreement with the following statements: In the next two weeks, I will stop using screens 1 hour before bed for better sleep.",
                      Q44_iwillexercise = "Please rate your agreement with the following statements: In the next two weeks, I will exercise for at least 30 minutes total each day for better sleep.",
                      Q44_iwillbreathe = "Please rate your agreement with the following statements: In the next two weeks, I will do a daily breathing exercise for better sleep.",
                      Q52_additionalcomments = "Please share any additional comments or feedback you have about the #GoodnightBloomberg sleep campaign below."
                      )

attach(sleephygiene)
tab1 <- tableby(~ Q3_role + 
                  Q4_gender +
                  Q5_age +
                  Q6_numberinhousehold +
                  Q37_employed +
                  Q10_hoursofsleeplast5workdays +
                  Q10_hoursofsleeppastweekend +
                  Q9_howoftensleepypastmonth +
                  Q61_howoftensleepypasttwoweeks +
                  Q84_awareofhowtoimprovesleepquality +
                  Q81_seenorheardfromGNbloombergcampaign +
                  #Q63_recalltoolsfreetect +
                  Q96_picture1 +
                  Q96_picture2 +
                  Q96_picture3 +
                  Q96_picture4 +
                  Q96_picture5 +
                  Q96_picture6 +
                  Q96_picture7 +
                  Q96_picture8 +
                  Q95_talkedtoanyone +
                  Q82_knowanyonewhoengaged +
                  Q69_didyouengagewiththecampaign +
                  Q67_move30minutes +
                  Q67_breathing +
                  Q67_powerdown +
                  Q68_timing + 
                  Q79_moresuccessfuloutcomsuggestions +
                  Q59_canmaintainhealthysleephabits +
                  Q59_cancutoutscreen +
                  Q59_canexercise +
                  Q59_canparticipateinbreathing +
                  Q44_goodnightsleepisimportant +
                  Q44_mentalclarity +
                  Q44_feelpositive +
                  Q44_cuttingoutscreenleadstobettersleep +
                  Q44_exercisingleadstobettersleep +
                  Q44_breathingexercisesleadstobettersleep +
                  Q44_iwillstopscreens +
                  Q44_iwillexercise +
                  Q44_iwillbreathe,
                data=sleephygiene, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab1, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=94)
What is your role at Bloomberg
N-Miss	3
Faculty/Staff Member	6 (6.6%)
Full-time student	54 (59.3%)
Part-time student	31 (34.1%)
Which best describes your gender identity?
N-Miss	3
Female	77 (84.6%)
Male	13 (14.3%)
Non-binary / third gender	1 (1.1%)
How old are you?
N-Miss	3
18-25	30 (33.0%)
26-34	40 (44.0%)
35-44	13 (14.3%)
45-54	8 (8.8%)
How many people live in your household, including yourself?
Median (Q1, Q3)	2.00 (2.00, 3.00)
If you are a student at Bloomberg, are you currently employed outside of your education program?
N-Miss	3
N/A - I am not a student at Bloomberg	6 (6.6%)
No	43 (47.3%)
Yes	42 (46.2%)
On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?
Median (Q1, Q3)	7.00 (6.00, 7.00)
On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?
Median (Q1, Q3)	8.00 (7.00, 8.00)
How often did you feel sleepy during the day in the past month?
N-Miss	38
Never	2 (3.6%)
Rarely	8 (14.3%)
Sometimes	39 (69.6%)
Very often	0 (0.0%)
Always	7 (12.5%)
How often did you feel sleepy during the day during the past 2 weeks?
N-Miss	34
Never	2 (3.3%)
Rarely	12 (20.0%)
Sometimes	36 (60.0%)
Very often	0 (0.0%)
Always	10 (16.7%)
Do you know any ways a person can improve their sleep quality?
N-Miss	1
No	4 (4.3%)
Yes	89 (95.7%)
In the last two-three weeks have you heard, seen, or received any information from the #GoodnightBloomberg campaign led by JHSPH students promoting better sleep?
N-Miss	1
Don’t know	21 (22.6%)
No	29 (31.2%)
Yes	43 (46.2%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 1
N-Miss	12
No	16 (19.5%)
Not sure	61 (74.4%)
Yes	5 (6.1%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 2
N-Miss	9
No	4 (4.7%)
Not sure	44 (51.8%)
Yes	37 (43.5%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 3
N-Miss	12
No	14 (17.1%)
Not sure	63 (76.8%)
Yes	5 (6.1%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 4
N-Miss	12
No	13 (15.9%)
Not sure	60 (73.2%)
Yes	9 (11.0%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 5
N-Miss	11
No	7 (8.4%)
Not sure	62 (74.7%)
Yes	14 (16.9%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 6
N-Miss	11
No	11 (13.3%)
Not sure	70 (84.3%)
Yes	2 (2.4%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 7
N-Miss	11
No	9 (10.8%)
Not sure	64 (77.1%)
Yes	10 (12.0%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 8
N-Miss	12
No	9 (11.0%)
Not sure	69 (84.1%)
Yes	4 (4.9%)
Have you talked to anyone about the #GoodnightBloomberg campaign?
N-Miss	1
No	81 (87.1%)
Yes	12 (12.9%)
Do you know anyone who engaged in any way with the #GoodnightBloomberg campaign about promoting better sleep?
N-Miss	1
No	84 (90.3%)
Yes	9 (9.7%)
Did you engage in any way with the #GoodnightBloomberg campaign led by JHSPH students during the past 2 weeks?
N-Miss	1
No	73 (78.5%)
Yes	20 (21.5%)
In the last two weeks, how many days did you participate in the following techniques? Move 30 minutes total per day
Median (Q1, Q3)	9.00 (5.00, 12.00)
In the last two weeks, how many days did you participate in the following techniques? Use a breathing exercise
Median (Q1, Q3)	3.00 (1.50, 6.00)
In the last two weeks, how many days did you participate in the following techniques? Power down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed
Median (Q1, Q3)	3.00 (1.50, 6.00)
Was the timing of the texts/posts convenient for you to adopt the recommended activity?
N-Miss	21
No	31 (42.5%)
Yes	42 (57.5%)
I think I would have had a more successful outcome (e.g. better sleep quality) if (choose all that may apply):
N-Miss	24
I had more flexibility in my day	29 (41.4%)
The campaign was longer	18 (25.7%)
There was an in-person/on-campus component to the campaign	16 (22.9%)
There were subject matter experts checking in with me one-on-one	7 (10.0%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can maintain healthy sleep habits.
N-Miss	3
Not at all confident	16 (17.6%)
Somewhat confident	58 (63.7%)
Extremely confident	17 (18.7%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can cut out screen use 1 hour before bed.
N-Miss	3
Not at all confident	44 (48.4%)
Somewhat confident	34 (37.4%)
Extremely confident	13 (14.3%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can exercise for 30 minutes total each day.
N-Miss	3
Not at all confident	12 (13.2%)
Somewhat confident	39 (42.9%)
Extremely confident	40 (44.0%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can participate in a breathing exercise during the day or before bed.
N-Miss	3
Not at all confident	9 (9.9%)
Somewhat confident	50 (54.9%)
Extremely confident	32 (35.2%)
Please rate your agreement with the following statements: Getting a good night’s sleep is important to me.
N-Miss	3
Strongly disagree	0 (0.0%)
Somewhat disagree	0 (0.0%)
Neither agree nor disagree	1 (1.1%)
Somewhat agree	18 (19.8%)
Strongly agree	72 (79.1%)
Please rate your agreement with the following statements: Having a regular sleep routine improves mental clarity/sharpness.
N-Miss	3
Strongly disagree	0 (0.0%)
Somewhat disagree	0 (0.0%)
Neither agree nor disagree	0 (0.0%)
Somewhat agree	15 (16.5%)
Strongly agree	76 (83.5%)
Please rate your agreement with the following statements: I feel positive about the quality of my sleep.
N-Miss	3
Strongly disagree	7 (7.7%)
Somewhat disagree	22 (24.2%)
Neither agree nor disagree	16 (17.6%)
Somewhat agree	35 (38.5%)
Strongly agree	11 (12.1%)
Please rate your agreement with the following statements: I think cutting out screen use 1 hour before bed leads to better sleep.
N-Miss	2
Strongly disagree	1 (1.1%)
Somewhat disagree	2 (2.2%)
Neither agree nor disagree	14 (15.2%)
Somewhat agree	28 (30.4%)
Strongly agree	47 (51.1%)
Please rate your agreement with the following statements: I think exercising regularly leads to better sleep.
N-Miss	2
Strongly disagree	0 (0.0%)
Somewhat disagree	1 (1.1%)
Neither agree nor disagree	4 (4.3%)
Somewhat agree	27 (29.3%)
Strongly agree	60 (65.2%)
Please rate your agreement with the following statements: I think participating in breathing exercises during the day or before bed leads to better sleep.
N-Miss	2
Strongly disagree	0 (0.0%)
Somewhat disagree	1 (1.1%)
Neither agree nor disagree	21 (22.8%)
Somewhat agree	38 (41.3%)
Strongly agree	32 (34.8%)
Please rate your agreement with the following statements: In the next two weeks, I will stop using screens 1 hour before bed for better sleep.
N-Miss	4
Strongly disagree	18 (20.0%)
Somewhat disagree	16 (17.8%)
Neither agree nor disagree	18 (20.0%)
Somewhat agree	24 (26.7%)
Strongly agree	14 (15.6%)
Please rate your agreement with the following statements: In the next two weeks, I will exercise for at least 30 minutes total each day for better sleep.
N-Miss	3
Strongly disagree	2 (2.2%)
Somewhat disagree	5 (5.5%)
Neither agree nor disagree	14 (15.4%)
Somewhat agree	27 (29.7%)
Strongly agree	43 (47.3%)
Please rate your agreement with the following statements: In the next two weeks, I will do a daily breathing exercise for better sleep.
N-Miss	3
Strongly disagree	5 (5.5%)
Somewhat disagree	15 (16.5%)
Neither agree nor disagree	20 (22.0%)
Somewhat agree	34 (37.4%)
Strongly agree	17 (18.7%)

#If student
student <- sleephygiene %>% filter(Q3_role %in% c("Part-time student", "Full-time student"))

tab2 <- tableby(~ Q2_program,
                data=student, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab2, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=85)
What is your current program at Bloomberg?
Doctoral Student	20 (23.5%)
Masters Student	59 (69.4%)
Other	3 (3.5%)
Post-doctoral student	3 (3.5%)

#If employed 
nonbloombergstudentemployed <- sleephygiene %>% filter(Q37_employed == "N/A - I am not a student at Bloomberg")

tab3 <- tableby(~ Q92_notSPHemployed,
                data=nonbloombergstudentemployed, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab3, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=6)
Are you currently employed?
Yes	6 (100.0%)

#If employed and not bloomberg
employed <- nonbloombergstudentemployed %>% filter(Q92_notSPHemployed == "Yes")

tab4 <- tableby(~ Q93_worksetting,
                data=employed, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab4, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=6)
Which of the following best describes your current work setting?
I sometimes work at home and sometimes at another location	2 (33.3%)
I work from home	4 (66.7%)

#wfh not bloomberg
#wfhnotbloomberg <- nonbloombergstudentemployed %>% filter(Q93_worksetting == "I work in a location away from my home")

#tab5 <- tableby(~ Q94_dayornight,
#                data=wfhnotbloomberg, test=TRUE, total=TRUE, 
#                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
#summary(tab5, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

#student at bloomberg
studentemployed <- student %>% filter(Q37_employed == "Yes")

tab6 <- tableby(~ Q38_worksetting,
                data=studentemployed, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab6, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=42)
Which of the following best describes your current work setting?
N-Miss	1
I sometimes work at home and sometimes at another location	10 (24.4%)
I work from home	26 (63.4%)
I work in a location away from my home	5 (12.2%)

studentemployedlocation <- student %>% filter(Q39_dayornight == "I work in a location away from my home")

#tab7 <- tableby(~ Q39_dayornight,
#                data=studentemployedlocation, test=TRUE, total=TRUE, 
#                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
#summary(tab7, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)


#Aware of how to improve sleep quality
awareofsleepqualityimprovements <- sleephygiene %>% filter(Q84_awareofhowtoimprovesleepquality == "Yes")

tab8 <- tableby(~ Q85_waystoimprovesleepquality,
                data=awareofsleepqualityimprovements, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab8, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=89)
What are some of the ways to improve sleep quality that you know?
N-Miss	1
Not drinking caffeinated beverages late in the day	81 (92.0%)
Reduce irregular or long daytime naps	1 (1.1%)
Switching off electronics one hour before sleep	5 (5.7%)
Try to sleep and wake at consistent times	1 (1.1%)

#Talked to someone
talkedtosomeone <- sleephygiene %>% filter(Q95_talkedtoanyone == "Yes")

tab9 <- tableby(~ Q83_talkedtowho,
                data=talkedtosomeone, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab9, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=12)
Please indicate with whom you talked about #GoodnightBloomberg (check all that apply).
N-Miss	1
Colleague	1 (9.1%)
Friends	8 (72.7%)
Spouse	2 (18.2%)

#engaged in any way
engagedwiththecampaign <- sleephygiene %>% filter(Q69_didyouengagewiththecampaign == "Yes")

tab10 <- tableby(~ Q62_howdidyouengage +
                   Q64_whichtechniquedidyoutry +
                   Q90_areyouhappywithyoursleepquality_awareofcampaign +
                   Q75_moving +
                   Q75_breathing +
                   Q75_powerdown,
                data=engagedwiththecampaign, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab10, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=20)
Please select which of the following parts of the #GoodnightBloomberg campaign you engaged in:
N-Miss	1
Instagram campaign	13 (68.4%)
Text message campaign	6 (31.6%)
Which of the following techniques did you try at least once in the last 2 weeks (choose all that apply)?
Breathe	5 (25.0%)
Movemore	13 (65.0%)
None of the above	1 (5.0%)
Powerdown	1 (5.0%)
Are you happy with your sleep quality overall currently?
N-Miss	1
No	8 (42.1%)
Yes	11 (57.9%)
How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Moving 30 minutes total per day
N-Miss	7
Extremely unhelpful	0 (0.0%)
Somewhat unhelpful	0 (0.0%)
Neither helpful nor unhelpful	0 (0.0%)
Somewhat helpful	9 (69.2%)
Extremely helpful	4 (30.8%)
How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Using a breathing exercise
N-Miss	10
Extremely unhelpful	0 (0.0%)
Somewhat unhelpful	0 (0.0%)
Neither helpful nor unhelpful	5 (50.0%)
Somewhat helpful	3 (30.0%)
Extremely helpful	2 (20.0%)
How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Powering down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed
N-Miss	13
Extremely unhelpful	0 (0.0%)
Somewhat unhelpful	0 (0.0%)
Neither helpful nor unhelpful	2 (28.6%)
Somewhat helpful	4 (57.1%)
Extremely helpful	1 (14.3%)

#did not engagee in any way
noengagementwiththecampagin <- sleephygiene %>% filter(Q69_didyouengagewiththecampaign %in% c("No", "Don't know"))

tab11 <- tableby(~ Q91_areyouhappywithyoursleepquality_notawareofcampaign +
                   Q89_ratesleepquality_notawareofcampaign,
                data=noengagementwiththecampagin, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab11, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=73)
Are you happy with your sleep quality overall currently?
N-Miss	25
No	29 (60.4%)
Yes	19 (39.6%)
Please rate your sleep quality from the following options: In the last two weeks? (on average)
N-Miss	24
Poor	4 (8.2%)
Fair	20 (40.8%)
Good	22 (44.9%)
Excellent	3 (6.1%)

#not convenient 
notconvenient <- sleephygiene %>% filter(Q68_timing == "No")

tab12 <- tableby(~ Q70_timingoftextsinconvenient,
                data=noengagementwiththecampagin, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab12, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=73)
Please provide information below about why the timing of the texts/posts was inconvenient?
N-Miss	55
Messages were too infrequent	3 (16.7%)
Other (please explain below)	14 (77.8%)
Received message too early in the day	1 (5.6%)

#tooearlyintheday
tooearlyortoolate <- notconvenient %>% filter(Q70_timingoftextsinconvenient %in% c("Received message too early in the day", "Received message too late in the day"))

tab13 <- tableby(~ Q87_idealtime,
                data=tooearlyortoolate, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab13, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=2)
What would have been the ideal time to receive the message (EST/EDT)?
Early morning (6:00 am - 9:00 am)	0 (0.0%)
Late morning (9:01 am - 12:00 pm)	0 (0.0%)
Early afternoon (12:01 pm - 3:00 pm)	0 (0.0%)
Late afternoon (3:01 pm - 6:00 pm)	0 (0.0%)
Early evening (6:01 pm - 9:00 pm)	2 (100.0%)
Late evening (9:01 pm - 12:00 am)	0 (0.0%)
Other (please specify)	0 (0.0%)

#whichmosteducational
instagramortext <- engagedwiththecampaign %>% filter(Q62_howdidyouengage %in% c("Instagram", "Text message campaign"))

#tab14 <- tableby(~ Q71_whichchannelmosteducational +
#                   Q72,
#                data=instagramortext, test=TRUE, total=TRUE, 
#                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
#summary(tab14, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

#instagram
instagram <- engagedwiththecampaign %>% filter(Q62_howdidyouengage == "Instagram campaign")

tab15 <- tableby(~ Q74_rafflemotivating,
                data=instagram, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab15, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=13)
Did you find the raffles motivating for participation in the #GoodnightBloomberg campaign?
No	3 (23.1%)
Yes	10 (76.9%)

#seenorheardofthecampiagn
seenordheard <- sleephygiene %>% filter(Q81_seenorheardfromGNbloombergcampaign == "Yes")

tab16 <- tableby(~ Q81_seenorheardfromGNbloombergcampaign,
                data=seenordheard, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab16, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=43)
In the last two-three weeks have you heard, seen, or received any information from the #GoodnightBloomberg campaign led by JHSPH students promoting better sleep?
Don’t know	0 (0.0%)
No	0 (0.0%)
Yes	43 (100.0%)

sleephygiene <- sleephygiene %>% mutate(Engagementyesno = case_when(
  Q69_didyouengagewiththecampaign == "Yes" ~ 1,
  Q69_didyouengagewiththecampaign == "No" ~ 0,
  Q69_didyouengagewiththecampaign == "Don't know" ~ 0,
  is.na(Q69_didyouengagewiththecampaign) ~ NA_real_)) %>%
  mutate(Engagementyesno = factor(Engagementyesno))

tab1 <- tableby(Engagementyesno ~ Q3_role + 
                  Q4_gender +
                  Q5_age +
                  Q6_numberinhousehold +
                  Q37_employed +
                  Q10_hoursofsleeplast5workdays +
                  Q10_hoursofsleeppastweekend +
                  Q9_howoftensleepypastmonth +
                  Q61_howoftensleepypasttwoweeks +
                  Q84_awareofhowtoimprovesleepquality +
                  Q81_seenorheardfromGNbloombergcampaign +
                  Q96_picture1 +
                  Q96_picture2 +
                  Q96_picture3 +
                  Q96_picture4 +
                  Q96_picture5 +
                  Q96_picture6 +
                  Q96_picture7 +
                  Q96_picture8 +
                  Q95_talkedtoanyone +
                  Q82_knowanyonewhoengaged +
                  Q69_didyouengagewiththecampaign +
                  Q67_move30minutes +
                  Q67_breathing +
                  Q67_powerdown +
                  Q68_timing + 
                  Q79_moresuccessfuloutcomsuggestions +
                  Q59_canmaintainhealthysleephabits +
                  Q59_cancutoutscreen +
                  Q59_canexercise +
                  Q59_canparticipateinbreathing +
                  Q44_goodnightsleepisimportant +
                  Q44_mentalclarity +
                  Q44_feelpositive +
                  Q44_cuttingoutscreenleadstobettersleep +
                  Q44_exercisingleadstobettersleep +
                  Q44_breathingexercisesleadstobettersleep +
                  Q44_iwillstopscreens +
                  Q44_iwillexercise +
                  Q44_iwillbreathe,
                data=sleephygiene, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab1, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	0 (N=73)	1 (N=20)	Total (N=93)	p value
What is your role at Bloomberg				0.430¹
N-Miss	0	2	2
Faculty/Staff Member	6 (8.2%)	0 (0.0%)	6 (6.6%)
Full-time student	42 (57.5%)	12 (66.7%)	54 (59.3%)
Part-time student	25 (34.2%)	6 (33.3%)	31 (34.1%)
Which best describes your gender identity?				0.797¹
N-Miss	0	2	2
Female	61 (83.6%)	16 (88.9%)	77 (84.6%)
Male	11 (15.1%)	2 (11.1%)	13 (14.3%)
Non-binary / third gender	1 (1.4%)	0 (0.0%)	1 (1.1%)
How old are you?				0.949¹
N-Miss	0	2	2
18-25	24 (32.9%)	6 (33.3%)	30 (33.0%)
26-34	33 (45.2%)	7 (38.9%)	40 (44.0%)
35-44	10 (13.7%)	3 (16.7%)	13 (14.3%)
45-54	6 (8.2%)	2 (11.1%)	8 (8.8%)
How many people live in your household, including yourself?				0.014²
Median (Q1, Q3)	2.00 (2.00, 3.00)	3.00 (2.00, 4.00)	2.00 (2.00, 3.00)
If you are a student at Bloomberg, are you currently employed outside of your education program?				0.037¹
N-Miss	0	2	2
N/A - I am not a student at Bloomberg	6 (8.2%)	0 (0.0%)	6 (6.6%)
No	38 (52.1%)	5 (27.8%)	43 (47.3%)
Yes	29 (39.7%)	13 (72.2%)	42 (46.2%)
On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?				0.487²
Median (Q1, Q3)	7.00 (6.00, 7.00)	7.00 (6.00, 7.00)	7.00 (6.00, 7.00)
On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?				0.773²
Median (Q1, Q3)	8.00 (7.00, 8.00)	8.00 (7.00, 8.75)	8.00 (7.00, 8.00)
How often did you feel sleepy during the day in the past month?
N-Miss	29	8	37
Never	2 (4.5%)	0 (0.0%)	2 (3.6%)
Rarely	6 (13.6%)	2 (16.7%)	8 (14.3%)
Sometimes	31 (70.5%)	8 (66.7%)	39 (69.6%)
Very often	0 (0.0%)	0 (0.0%)	0 (0.0%)
Always	5 (11.4%)	2 (16.7%)	7 (12.5%)
How often did you feel sleepy during the day during the past 2 weeks?
N-Miss	26	7	33
Never	2 (4.3%)	0 (0.0%)	2 (3.3%)
Rarely	9 (19.1%)	3 (23.1%)	12 (20.0%)
Sometimes	28 (59.6%)	8 (61.5%)	36 (60.0%)
Very often	0 (0.0%)	0 (0.0%)	0 (0.0%)
Always	8 (17.0%)	2 (15.4%)	10 (16.7%)
Do you know any ways a person can improve their sleep quality?				0.285¹
No	4 (5.5%)	0 (0.0%)	4 (4.3%)
Yes	69 (94.5%)	20 (100.0%)	89 (95.7%)
In the last two-three weeks have you heard, seen, or received any information from the #GoodnightBloomberg campaign led by JHSPH students promoting better sleep?				< 0.001¹
Don’t know	20 (27.4%)	1 (5.0%)	21 (22.6%)
No	29 (39.7%)	0 (0.0%)	29 (31.2%)
Yes	24 (32.9%)	19 (95.0%)	43 (46.2%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 1				0.005¹
N-Miss	8	3	11
No	8 (12.3%)	8 (47.1%)	16 (19.5%)
Not sure	53 (81.5%)	8 (47.1%)	61 (74.4%)
Yes	4 (6.2%)	1 (5.9%)	5 (6.1%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 2				< 0.001¹
N-Miss	7	1	8
No	4 (6.1%)	0 (0.0%)	4 (4.7%)
Not sure	42 (63.6%)	2 (10.5%)	44 (51.8%)
Yes	20 (30.3%)	17 (89.5%)	37 (43.5%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 3				< 0.001¹
N-Miss	8	3	11
No	8 (12.3%)	6 (35.3%)	14 (17.1%)
Not sure	56 (86.2%)	7 (41.2%)	63 (76.8%)
Yes	1 (1.5%)	4 (23.5%)	5 (6.1%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 4				0.018¹
N-Miss	8	3	11
No	7 (10.8%)	6 (35.3%)	13 (15.9%)
Not sure	52 (80.0%)	8 (47.1%)	60 (73.2%)
Yes	6 (9.2%)	3 (17.6%)	9 (11.0%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 5				< 0.001¹
N-Miss	8	2	10
No	6 (9.2%)	1 (5.6%)	7 (8.4%)
Not sure	56 (86.2%)	6 (33.3%)	62 (74.7%)
Yes	3 (4.6%)	11 (61.1%)	14 (16.9%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 6				0.463¹
N-Miss	7	3	10
No	8 (12.1%)	3 (17.6%)	11 (13.3%)
Not sure	57 (86.4%)	13 (76.5%)	70 (84.3%)
Yes	1 (1.5%)	1 (5.9%)	2 (2.4%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 7				< 0.001¹
N-Miss	8	2	10
No	8 (12.3%)	1 (5.6%)	9 (10.8%)
Not sure	55 (84.6%)	9 (50.0%)	64 (77.1%)
Yes	2 (3.1%)	8 (44.4%)	10 (12.0%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 8				0.325¹
N-Miss	8	3	11
No	7 (10.8%)	2 (11.8%)	9 (11.0%)
Not sure	56 (86.2%)	13 (76.5%)	69 (84.1%)
Yes	2 (3.1%)	2 (11.8%)	4 (4.9%)
Have you talked to anyone about the #GoodnightBloomberg campaign?				< 0.001¹
No	71 (97.3%)	10 (50.0%)	81 (87.1%)
Yes	2 (2.7%)	10 (50.0%)	12 (12.9%)
Do you know anyone who engaged in any way with the #GoodnightBloomberg campaign about promoting better sleep?				< 0.001¹
No	70 (95.9%)	14 (70.0%)	84 (90.3%)
Yes	3 (4.1%)	6 (30.0%)	9 (9.7%)
Did you engage in any way with the #GoodnightBloomberg campaign led by JHSPH students during the past 2 weeks?				< 0.001¹
No	73 (100.0%)	0 (0.0%)	73 (78.5%)
Yes	0 (0.0%)	20 (100.0%)	20 (21.5%)
In the last two weeks, how many days did you participate in the following techniques? Move 30 minutes total per day				0.333²
Median (Q1, Q3)	9.00 (6.00, 12.00)	8.00 (4.25, 10.00)	9.00 (5.00, 12.00)
In the last two weeks, how many days did you participate in the following techniques? Use a breathing exercise				0.270²
Median (Q1, Q3)	3.00 (1.00, 6.00)	5.00 (2.00, 7.00)	3.00 (1.50, 6.00)
In the last two weeks, how many days did you participate in the following techniques? Power down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed				0.270²
Median (Q1, Q3)	3.00 (1.00, 6.00)	5.00 (2.00, 7.00)	3.00 (1.50, 6.00)
Was the timing of the texts/posts convenient for you to adopt the recommended activity?				0.018¹
N-Miss	17	3	20
No	28 (50.0%)	3 (17.6%)	31 (42.5%)
Yes	28 (50.0%)	14 (82.4%)	42 (57.5%)
I think I would have had a more successful outcome (e.g. better sleep quality) if (choose all that may apply):				0.266¹
N-Miss	22	1	23
I had more flexibility in my day	23 (45.1%)	6 (31.6%)	29 (41.4%)
The campaign was longer	10 (19.6%)	8 (42.1%)	18 (25.7%)
There was an in-person/on-campus component to the campaign	12 (23.5%)	4 (21.1%)	16 (22.9%)
There were subject matter experts checking in with me one-on-one	6 (11.8%)	1 (5.3%)	7 (10.0%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can maintain healthy sleep habits.				0.380¹
N-Miss	0	2	2
Not at all confident	12 (16.4%)	4 (22.2%)	16 (17.6%)
Somewhat confident	49 (67.1%)	9 (50.0%)	58 (63.7%)
Extremely confident	12 (16.4%)	5 (27.8%)	17 (18.7%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can cut out screen use 1 hour before bed.				0.481¹
N-Miss	0	2	2
Not at all confident	33 (45.2%)	11 (61.1%)	44 (48.4%)
Somewhat confident	29 (39.7%)	5 (27.8%)	34 (37.4%)
Extremely confident	11 (15.1%)	2 (11.1%)	13 (14.3%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can exercise for 30 minutes total each day.				0.648¹
N-Miss	0	2	2
Not at all confident	9 (12.3%)	3 (16.7%)	12 (13.2%)
Somewhat confident	33 (45.2%)	6 (33.3%)	39 (42.9%)
Extremely confident	31 (42.5%)	9 (50.0%)	40 (44.0%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can participate in a breathing exercise during the day or before bed.				0.647¹
N-Miss	1	1	2
Not at all confident	8 (11.1%)	1 (5.3%)	9 (9.9%)
Somewhat confident	40 (55.6%)	10 (52.6%)	50 (54.9%)
Extremely confident	24 (33.3%)	8 (42.1%)	32 (35.2%)
Please rate your agreement with the following statements: Getting a good night’s sleep is important to me.
N-Miss	0	2	2
Strongly disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Neither agree nor disagree	1 (1.4%)	0 (0.0%)	1 (1.1%)
Somewhat agree	16 (21.9%)	2 (11.1%)	18 (19.8%)
Strongly agree	56 (76.7%)	16 (88.9%)	72 (79.1%)
Please rate your agreement with the following statements: Having a regular sleep routine improves mental clarity/sharpness.
N-Miss	1	1	2
Strongly disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Neither agree nor disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat agree	11 (15.3%)	4 (21.1%)	15 (16.5%)
Strongly agree	61 (84.7%)	15 (78.9%)	76 (83.5%)
Please rate your agreement with the following statements: I feel positive about the quality of my sleep.				0.982¹
N-Miss	0	2	2
Strongly disagree	6 (8.2%)	1 (5.6%)	7 (7.7%)
Somewhat disagree	18 (24.7%)	4 (22.2%)	22 (24.2%)
Neither agree nor disagree	13 (17.8%)	3 (16.7%)	16 (17.6%)
Somewhat agree	27 (37.0%)	8 (44.4%)	35 (38.5%)
Strongly agree	9 (12.3%)	2 (11.1%)	11 (12.1%)
Please rate your agreement with the following statements: I think cutting out screen use 1 hour before bed leads to better sleep.				0.833¹
N-Miss	0	1	1
Strongly disagree	1 (1.4%)	0 (0.0%)	1 (1.1%)
Somewhat disagree	2 (2.7%)	0 (0.0%)	2 (2.2%)
Neither agree nor disagree	12 (16.4%)	2 (10.5%)	14 (15.2%)
Somewhat agree	21 (28.8%)	7 (36.8%)	28 (30.4%)
Strongly agree	37 (50.7%)	10 (52.6%)	47 (51.1%)
Please rate your agreement with the following statements: I think exercising regularly leads to better sleep.
N-Miss	0	1	1
Strongly disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat disagree	1 (1.4%)	0 (0.0%)	1 (1.1%)
Neither agree nor disagree	3 (4.1%)	1 (5.3%)	4 (4.3%)
Somewhat agree	22 (30.1%)	5 (26.3%)	27 (29.3%)
Strongly agree	47 (64.4%)	13 (68.4%)	60 (65.2%)
Please rate your agreement with the following statements: I think participating in breathing exercises during the day or before bed leads to better sleep.
N-Miss	0	1	1
Strongly disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat disagree	1 (1.4%)	0 (0.0%)	1 (1.1%)
Neither agree nor disagree	15 (20.5%)	6 (31.6%)	21 (22.8%)
Somewhat agree	31 (42.5%)	7 (36.8%)	38 (41.3%)
Strongly agree	26 (35.6%)	6 (31.6%)	32 (34.8%)
Please rate your agreement with the following statements: In the next two weeks, I will stop using screens 1 hour before bed for better sleep.				0.845¹
N-Miss	1	2	3
Strongly disagree	13 (18.1%)	5 (27.8%)	18 (20.0%)
Somewhat disagree	14 (19.4%)	2 (11.1%)	16 (17.8%)
Neither agree nor disagree	15 (20.8%)	3 (16.7%)	18 (20.0%)
Somewhat agree	19 (26.4%)	5 (27.8%)	24 (26.7%)
Strongly agree	11 (15.3%)	3 (16.7%)	14 (15.6%)
Please rate your agreement with the following statements: In the next two weeks, I will exercise for at least 30 minutes total each day for better sleep.				0.505¹
N-Miss	0	2	2
Strongly disagree	2 (2.7%)	0 (0.0%)	2 (2.2%)
Somewhat disagree	3 (4.1%)	2 (11.1%)	5 (5.5%)
Neither agree nor disagree	13 (17.8%)	1 (5.6%)	14 (15.4%)
Somewhat agree	21 (28.8%)	6 (33.3%)	27 (29.7%)
Strongly agree	34 (46.6%)	9 (50.0%)	43 (47.3%)
Please rate your agreement with the following statements: In the next two weeks, I will do a daily breathing exercise for better sleep.				0.829¹
N-Miss	0	2	2
Strongly disagree	4 (5.5%)	1 (5.6%)	5 (5.5%)
Somewhat disagree	13 (17.8%)	2 (11.1%)	15 (16.5%)
Neither agree nor disagree	16 (21.9%)	4 (22.2%)	20 (22.0%)
Somewhat agree	28 (38.4%)	6 (33.3%)	34 (37.4%)
Strongly agree	12 (16.4%)	5 (27.8%)	17 (18.7%)

Pearson’s Chi-squared test
Kruskal-Wallis rank sum test

sleephygienepre <- readRDS(file="foranalysis.rds")

sleephygienepre <- sleephygienepre %>% 
  mutate(Q5_age = case_when(
    Q5_age >= 18 & Q5_age <= 25 ~ "18-25",
    Q5_age >= 26 & Q5_age <= 34 ~ "26-34",
    Q5_age >= 35 & Q5_age <= 44 ~ "35-44",
    Q5_age >= 45 & Q5_age <= 54 ~ "45-54",
    Q5_age >= 55 & Q5_age < 64 ~ "55-64",
    Q5_age >= 64 & Q5_age <= 75 ~ "64-75",
    Q5_age > 75 ~ "75+",
    is.na(Q5_age) ~ NA_character_
  )) %>% 
  mutate(Q5_age = factor(Q5_age)) %>%
  mutate(post = 0) %>% 
  mutate(
    Q10_hoursofsleeplast5workdays = Q10_workdayhoursofsleep,
    Q10_hoursofsleeppastweekend = Q11_weekendhoursofsleep,
    Q61_howoftensleepypasttwoweeks = Q9_howoftensleepy
  ) %>%
  select(post, Q3_role, Q2_program, Q4_gender, Q5_age, Q6_numberinhousehold, Q10_hoursofsleeplast5workdays, Q10_hoursofsleeppastweekend, Q61_howoftensleepypasttwoweeks)
  
sleephygienepost <- sleephygiene %>% mutate(post = 1) %>% select(post, Q3_role, Q2_program, Q4_gender, Q5_age, Q6_numberinhousehold, Q10_hoursofsleeplast5workdays, Q10_hoursofsleeppastweekend, Q61_howoftensleepypasttwoweeks) 

sleephygienepreandpost <- rbind(sleephygienepre, sleephygienepost)

sleephygienepreandpost <- sleephygienepreandpost %>% mutate(Q61_smaller = case_when(
  is.na(Q61_howoftensleepypasttwoweeks) ~ NA_character_,
  Q61_howoftensleepypasttwoweeks == "Never" ~ "Never",
  Q61_howoftensleepypasttwoweeks == "Rarely" ~ "Rarely",
  Q61_howoftensleepypasttwoweeks == "Sometimes" ~ "Sometimes",
  Q61_howoftensleepypasttwoweeks == "Very often" | Q61_howoftensleepypasttwoweeks == "Always" ~ "Very often or Alway",
)) %>%
  mutate(Q61_smaller = factor(Q61_smaller))

tab1 <- tableby(post ~ Q3_role +
                  Q2_program + 
                  Q4_gender + 
                  Q5_age + 
                  Q6_numberinhousehold +
                  Q10_hoursofsleeplast5workdays +
                  Q10_hoursofsleeppastweekend +
                  Q61_smaller,
                data=sleephygienepreandpost, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab1, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	0 (N=209)	1 (N=94)	Total (N=303)	p value
Q3_role				0.189¹
N-Miss	3	3	6
Faculty/Staff Member	6 (2.9%)	6 (6.6%)	12 (4.0%)
Full-time student	140 (68.0%)	54 (59.3%)	194 (65.3%)
Part-time student	60 (29.1%)	31 (34.1%)	91 (30.6%)
Q2_program				0.010¹
N-Miss	9	9	18
Doctoral Student	54 (27.0%)	20 (23.5%)	74 (26.0%)
Masters Student	140 (70.0%)	59 (69.4%)	199 (69.8%)
Other	1 (0.5%)	3 (3.5%)	4 (1.4%)
Post doctoral student	5 (2.5%)	0 (0.0%)	5 (1.8%)
Post-doctoral student	0 (0.0%)	3 (3.5%)	3 (1.1%)
Q4_gender				0.772¹
N-Miss	3	3	6
Female	166 (80.6%)	77 (84.6%)	243 (81.8%)
Male	35 (17.0%)	13 (14.3%)	48 (16.2%)
Non-binary / third gender	4 (1.9%)	1 (1.1%)	5 (1.7%)
Prefer not to say	1 (0.5%)	0 (0.0%)	1 (0.3%)
Q5_age				0.575¹
N-Miss	5	3	8
18-25	64 (31.4%)	30 (33.0%)	94 (31.9%)
26-34	98 (48.0%)	40 (44.0%)	138 (46.8%)
35-44	32 (15.7%)	13 (14.3%)	45 (15.3%)
45-54	9 (4.4%)	8 (8.8%)	17 (5.8%)
55-64	1 (0.5%)	0 (0.0%)	1 (0.3%)
How many people live in your household, including yourself?				0.713²
Median (Q1, Q3)	2.00 (2.00, 3.00)	2.00 (2.00, 3.00)	2.00 (2.00, 3.00)
During the past 5 workdays, how many hours of sleep did you get per night on average?				0.752²
Median (Q1, Q3)	7.00 (6.00, 7.50)	7.00 (6.00, 7.00)	7.00 (6.00, 7.50)
During the past weekend, how many hours of sleep did you get per night on average?				0.319²
Median (Q1, Q3)	8.00 (7.00, 9.00)	8.00 (7.00, 8.00)	8.00 (7.00, 9.00)
Q61_smaller				0.254¹
N-Miss	69	34	103
Never	3 (2.1%)	2 (3.3%)	5 (2.5%)
Rarely	27 (19.3%)	12 (20.0%)	39 (19.5%)
Sometimes	99 (70.7%)	36 (60.0%)	135 (67.5%)
Very often or Alway	11 (7.9%)	10 (16.7%)	21 (10.5%)

Pearson’s Chi-squared test
Kruskal-Wallis rank sum test

library(sjPlot)

## Learn more about sjPlot with 'browseVignettes("sjPlot")'.

sleephygiene <- sleephygiene %>% mutate(Q69_didyouengagewiththecampaignbinary = case_when(
  Q69_didyouengagewiththecampaign == "No" ~ 0,
  Q69_didyouengagewiththecampaign == "Yes" ~ 1)) %>%
  mutate(Q4_gender_binary = case_when(
    Q4_gender == "Male" ~ 1,
    Q4_gender == "Female" ~ 0,
    TRUE ~ NA_real_
  )) %>%
  mutate(Q4_gender_binary = factor(Q4_gender_binary, labels = c("Female", "Male"))) %>%
  mutate(happywithsleepqualitycombined = case_when(
    Q90_areyouhappywithyoursleepquality_awareofcampaign == "Yes" ~ 1,
    Q90_areyouhappywithyoursleepquality_awareofcampaign == "No" ~ 0,
    Q91_areyouhappywithyoursleepquality_notawareofcampaign == "Yes" ~ 1,
    Q91_areyouhappywithyoursleepquality_notawareofcampaign == "No" ~ 0,
    Q89_ratesleepquality_notawareofcampaign == "Good" ~ 1,
    Q89_ratesleepquality_notawareofcampaign == "Excellent" ~ 1,
    Q89_ratesleepquality_notawareofcampaign == "Poor" ~ 0,
    Q89_ratesleepquality_notawareofcampaign == "Fair" ~ 0,
  )) %>%
  mutate(happywithsleepqualitycombined = factor(happywithsleepqualitycombined)) %>%
  mutate(Q67_1 = case_when(
    is.na(Q67_1) ~ 0,
    TRUE ~ as.numeric(Q67_1)
  )) %>%
  mutate(Q67_2 = case_when(
    is.na(Q67_2) ~ 0,
    TRUE ~ as.numeric(Q67_2)
  )) %>%
  mutate(Q67_3 = case_when(
    is.na(Q67_3) ~ 0,
    TRUE ~ as.numeric(Q67_3)
  )) %>%
  mutate(pointscombinedperdays = Q67_1 + Q67_2 + Q67_3) %>%
  mutate(ratesleepqualitycombined = case_when(
    Q89_ratesleepquality_notawareofcampaign == "Good" ~ 1,
    Q89_ratesleepquality_notawareofcampaign == "Excellent" ~ 1,
    Q89_ratesleepquality_notawareofcampaign == "Poor" ~ 0,
    Q89_ratesleepquality_notawareofcampaign == "Fair" ~ 0,
  ))

#Participating in the campaign
mylogit <- glm(Q69_didyouengagewiththecampaignbinary ~ Q4_gender_binary + Q10_hoursofsleeplast5workdays + Q10_hoursofsleeppastweekend, family = binomial(link = "logit"), data = sleephygiene)
tab_model(mylogit)

	Q69_didyouengagewiththecampaignbinary
Predictors	Odds Ratios	CI	p
(Intercept)	0.58	0.01 – 26.20	0.783
Q4_gender_binary: Male	0.77	0.11 – 3.36	0.752
On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?	0.68	0.39 – 1.17	0.156
On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?	1.26	0.80 – 2.04	0.326
Observations	90
R² Tjur	0.026

#Happy with sleep quality
mylogit <- glm(happywithsleepqualitycombined ~ Q4_gender_binary + Q10_hoursofsleeplast5workdays + Q10_hoursofsleeppastweekend + Q69_didyouengagewiththecampaignbinary, family = binomial(link = "logit"), data = sleephygiene)
tab_model(mylogit)

	happywithsleepqualitycombined
Predictors	Odds Ratios	CI	p
(Intercept)	0.00	0.00 – 0.01	<0.001
Q4_gender_binary: Male	1.86	0.48 – 7.56	0.372
On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?	4.02	2.05 – 9.10	<0.001
On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?	0.88	0.55 – 1.40	0.604
Q69_didyouengagewiththecampaignbinary	2.33	0.68 – 8.57	0.185
Observations	90
R² Tjur	0.255

mylogit <- glm(happywithsleepqualitycombined ~ pointscombinedperdays, family = binomial(link = "logit"), data = sleephygiene)
tab_model(mylogit)

	happywithsleepqualitycombined
Predictors	Odds Ratios	CI	p
(Intercept)	0.50	0.22 – 1.10	0.089
pointscombinedperdays	1.04	0.98 – 1.10	0.189
Observations	93
R² Tjur	0.019